Big data analysis and mechanism model collaborative road water depth monitoring method and system

Abstract

The invention discloses a big data analysis and mechanism model collaborative road water depth monitoring method and system. The method comprises the following steps: S1, collecting road water information; S2, identifying a road water area image to obtain the actual area of the road water area, and processing the rainfall, the road single-point water depth and the actual area of the road water area to obtain the road water depth; and S3, outputting the road water depth. The big data analysis and mechanism model collaborative road water depth monitoring system comprises a parameter acquisitionmodule, a data processing module and an output module. According to the method, the maximum depth of the road water area can be accurately calculated, the maximum depth can be accurately predicted, the situations of false alarm and error alarm of the road water depth are effectively prevented, the defects of other road water monitoring modes are overcome, and a powerful reference is provided for road drainage construction.

Description

technical field [0001] The invention relates to the field of road monitoring, in particular to a method and system for monitoring the depth of road water accumulation in cooperation with big data analysis and mechanism models. Background technique [0002] With the continuous advancement of urbanization in my country, the urban climate and the conditions of the underlying surface have undergone significant changes. Under the influence of the lagging construction of the urban drainage pipe network system and the unreasonable planning of the drainage system, once severe weather such as typhoons and heavy rains occurs, urban roads will be flooded, which seriously affects the travel of urban residents. [0003] The existing monitoring methods for water accumulation on urban roads are mainly divided into two categories: equipment monitoring and data mining analysis. Among them, equipment monitoring monitors road water accumulation by deploying water level sensors; data mining an...

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Problems solved by technology

[0004] However, the equipment monitoring method can only measure the water depth at the sensor measurement point, and it is difficult to accurately measure the maximum depth or effective depth of the urban road water accumulation area, which is prone to false positives and false negatives

However, data mining analysis requires all high-precision digital elevation data of urban roads, urban drainage pipe network and other information, and there are problems such as difficult data acquisition, incomplete data, complex data, difficult data update, and insufficient recognition accuracy.

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